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Classification of Malignant Tumors: A Practical Approach - Moitra, Dipanjan
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  • Broschiertes Buch

This book is mainly for the students of machine learning. This book also addresses the needs of the researchers who work in the knowledge field of bio-medical imaging and computer assisted oncology. This book demonstrates a holistic approach of malignant tumor classification via machine learning. It enumerates different stages of image analysis and image segmentation with the help of MATLAB code. WEKA data mining software has been used to describe both supervised and unsupervised learning methods. Each and every phase of tumor classification: feature extraction, data pre-processing, attribute…mehr

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Produktbeschreibung
This book is mainly for the students of machine learning. This book also addresses the needs of the researchers who work in the knowledge field of bio-medical imaging and computer assisted oncology. This book demonstrates a holistic approach of malignant tumor classification via machine learning. It enumerates different stages of image analysis and image segmentation with the help of MATLAB code. WEKA data mining software has been used to describe both supervised and unsupervised learning methods. Each and every phase of tumor classification: feature extraction, data pre-processing, attribute selection, classification and model evaluation has been properly explained with the help of screenshots. It has also been depicted that, how the users may use python to execute such classification tasks.I hope this book will help the students, researchers as well as teachers working on machine learning as a ready reference.
Autorenporträt
O Sr. Dipanjan Moitra é uma faculdade de TI no Departamento de Gestão, Universidade de Bengala do Norte, Índia. Completou o seu MCA da IGNOU em 2005. Foi autor de vários artigos de investigação sobre aprendizagem de máquinas e também autor de um livro sobre MIS. Trabalha também como revisor e editor técnico em muitas revistas nacionais e internacionais de renome.